In the past, the allocation of shelf space between products has been substantially fixed over short intervals of time, with adjustments being made largely by manual processes, including negotiations with manufacturers. Further, the information used to justify space allocation schemes and arrangement has been subject to numerous subjective processes, often resulting in decisions of questionable validity. While many efforts have been made to model sales as a function of shelf space and other factors, there is a need for a method and system for making objective decisions making shelf space allocation based on consumer data in which product interactions are considered and quantified.
A variety of tools and techniques have been applied in the past to assist retailers in planning shelf space allocation. For example, AC Nielsen offers a software tool, Shelf Builder, to assist in planning shelf space allocation. However, it does not appear to address the decision making process or apply household data to analyze a proposed design. Web sites, such as http://acnielsen.com/news/american/us/1997/19970923.htm and http://acnielsen.com/products/tools/shelfbuilder/features.htm, provide information about the Shelf Builder software. Other software tools from AC Nielsen include the SPACEMAN Merchandising Central and SPACEMAN Professional packages, in which retail planograms can be integrated with corporate Intranets, point-of-sale data processing, and other retail data to permit analysis of multiple scenarios. A planogram is a diagram that shows how and where retail products should be placed on retail shelves or displays. It further analyzes space utilization, provides financial analysis, along with many other reports that permit retailers and manufacturers to effectively manage their businesses. “Planogramming” is the art of using planogram software, which can also referred to as “space and category management” software. Again, the use of household data to align shelf space allocation with buyer group trends in order to objectively allocate shelf space does not appear to be part of these tools.
Another technique for shelf space analysis is Activity-Based Costing (ABC), as described at http://acnielsen.com/pubs/ci/1999/q3/features/assort.htm. ABC can be defined as: “determining an individual product's profit after all costs, including the resources required to offer the product for sale-such as labor, equipment and building utilities.” ABC is useful in accounting for the costs of getting and maintaining an item on shelf, but does not appear applicable to solving the problems of objectively allocating shelf space.
APOLLO™ 7.0 software suite, offered by Information Resources, Inc. (IRI), provides yet another technique. The APOLLO™ 7.0 software suite includes IRI's “Go-To-Shelf Strategy Solution,” which is said to help a firm's consumer packaged goods and retailer clients ensure consistent execution of category management plans and new product launches at the shelf by combining store and consumer tracking information with other services. This software is discussed in the article “APOLLO™ 7.0 Premieres at FMI Marketechnics; Helps Ensure Consistent Execution of Category Management Plans,” in Business Wire, Feb. 25, 1999
In spite of past efforts, there is a need for improved methods and systems of objective shelf space allocation that take decision making processes to a more quantitative or less subjective level, including methods and systems that permit decision making based on automated data analysis methods to optimize the use of shelf space. There is also a need for methods and systems that permit dynamic allocation of shelf space without the need for lengthy manual processes or without being highly subject to subjective factors. Further, in terms of promotions at retailers, such as temporary price discounts or coupon campaigns, shelf space allocations often need to be modified to better meet the demands of a promotion or to meet the sales potential that a promotion can provide. There is, therefore, also a need for an improved and efficient method and system for temporarily adjusting shelf space allocations in response to promotions, seasonal changes, or other foreseeable events to optimize sales, based on quantitative analysis of consumer data.
The invention described below addresses one or more of these and other disadvantages and needs.